use repeated_cross_section, clear

// muslim indicator 
gen muslim=(paiperc=="06"|paiperc=="08")

// interaction
gen inter=muslim*treatedcoh

// father birthplace FE
egen pbpl=group(paiperc)

local sample if pnai28=="10" & female==1 
local cl pbpl
estimates clear
reghdfe inactive inter `sample', cluster(`cl') absorb(i.pbpl i.birthyear i.surveyr i.ag##i.pbpl)
eststo c1

reghdfe employed inter `sample', cluster(`cl') absorb(i.pbpl i.birthyear i.surveyr i.ag##i.pbpl)
eststo c2

reghdfe child inter `sample', cluster(`cl') absorb(i.pbpl i.birthyear i.surveyr i.ag##i.pbpl)
eststo c3

reghdfe children inter `sample', cluster(`cl') absorb(i.pbpl i.birthyear i.surveyr i.ag##i.pbpl)
eststo c6

reghdfe married inter `sample', cluster(`cl') absorb(i.pbpl i.birthyear i.surveyr i.ag##i.pbpl)
eststo c7


esttab c* using "Table2.csv", star(+ 0.1 * 0.05 ** 0.01 *** 0.001) replace ///
		cells(b(fmt(a3) star) se(par)) stats(N r2)  ///
		keep(inter*) 
